Communities of Practice as Conduit for Knowledge Management: A Sociological Analysis of the Macro Level Health Care Decision-Making in Canada
Bibliographic record
Abstract
In this paper, Regional Health Authorities (RHAs) - occupying the macro-level health care decision-making in Canada are examined as a community of practice. The rationale is to assess the extent to which RHA members interact as a community of practice and how such interaction impacts on the knowledge management processes informing RHAs decision-making process. The fact that RHA members are geographically dispersed within a given health region makes the distributed community of practice the best option for RHA members to optimize the management of knowledge in their decision-making process. The prospects and challenges likely to confront RHAs as they embrace the distributed community of practice prism are examined. Identifying the prospects and challenges is vital in the institutionalization of enabling conditions in support of knowledge management at the macro level health care decision-making in Canada.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.024 | 0.022 |
| Scholarly communication | 0.010 | 0.003 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".